Ship faster with agent-native access to GPUs, clusters, and data—no network wrangling.
High-value, compute-intensive clusters need fine-grained permissions and context-aware policies that legacy VPNs cannot enforce.
CI/CD pipelines and AI agents must reach GPU resources instantly with explicit authorization and audit-grade consent.
MCP interactions between users, agents, and servers must be logged end-to-end to answer who accessed what data and why.
Current resource managers allocate GPUs without robust identity binding, leaving gaps in allocation, monitoring, and revocation.
Compliance frameworks mandate detailed trails of model usage, data flows, and authorization decisions for every AI session.
Sensitive workloads often run in private clouds or on-prem; security controls must travel with the infrastructure and honor data-residency policies.
Lumeus provides secure access to AI resources through connectors and gateways designed for GPU clusters and AI workloads.
Lightweight connector deployed on GPU instances with outbound connections to the Lumeus gateway for secure access with explicit authorization.
MCP Gateway that monitors every AI coding agent interaction—tracking which users accessed what data, through which tools, and why, with complete audit trails and user consent controls.
Native identity integrations embedded into existing GPU resource management systems for seamless access control with proper permissions.
See how organizations secure AI infrastructure access with identity-integrated controls
without compromising developer productivity or AI agent workflows.
Connect to compute‑intensive clusters through Lumeus connectors with explicit authorization and least‑privilege constraints.
Use existing notebooks, IDEs, and frameworks while Lumeus handles MCP‑aware authentication in the background.
AI agents inherit the same policies and consent flows, enabling autonomous jobs without security workarounds.
Bind identities directly into current GPU schedulers and portals—no workflow replacement.
Manage policies for humans and agents across multiple clusters from a single control plane.
Produce detailed trails of model usage, data flows, and authorization outcomes for regulators.
Enforce enterprise‑grade controls, fine‑grained permissions, and continuous monitoring.
Track who accessed which model and dataset, by code or by user, with detailed tracking of data access and authorization decisions.
Apply consistent authorization across all AI infrastructure, leveraging existing IdPs and consent mechanisms.
Consistent policies and logging for IDE/CLI workflows and coding agents—no network hoops.
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